Optimal Guaranteed Service Time and Service Level Decision with Time and Service Level Sensitive Demand

We consider a two-stage supply chain with one supplier and one retailer. The retailer sells a product to customer and the supplier provides a product in a make-to-order mode. In this case, the supplier’s decisions on service time and service level and the retailer’s decision on retail price have effects on customer demand. We develop optimization models to determine the optimal retail price, the optimal guaranteed service time, the optimal service level, and the optimal capacity to maximize the expected profit of the whole supply chain. The results of numerical experiments show that it is more profitable to determine the optimal price, the optimal guaranteed service time, and the optimal service level simultaneously and the proposed model is more profitable in service level sensitive market

Competition and Contracting in Service Industries

Two very different contractual structures are commonly observed in service industries with congestion effects: service level guarantees (SLGs) and best effort (BE) service. We analyze the impact of these contractual agreements on market outcomes in oligopolistic industries. First, we consider a model where firms compete by setting prices and SLGs simultaneously. The SLG is a contractual obligation on the part of the service provider: regardless of how many customers subscribe, the firm is responsible for investing so that the congestion experienced by all subscribers is equal to the SLG. We then consider the BE contractual model where firms compete by setting prices and investment levels simultaneously. With BE contractual agreements, firms provide the best possible service given their infrastructure, but without an explicit guarantee. Using the Nash equilibria (NE) of the games played by firms, we compare these competitive models in terms of the resulting prices, service levels, firms' profits, and consumers' surplus. We first show that the SLG game can be reduced to a standard pricing game, greatly simplifying the analysis of this otherwise complex competitive scenario. We then compare the SLG game with the BE game; equilibria for the BE is characterized in a previous paper. Using these results we show that in the case of constant returns to investment, while the NE price for the SLG game is perfectly competitive, firms obtain positive markups in the unique NE for the BE game. We also study the firms' choice of the strategy space, i.e., whether to offer SLG or BE contracts to the consumer, and find that competition is intensified if even one firm chooses to offer SLG contracts. Our results contribute to the basic understanding of competition and contracting in service industries and yield insight into business and policy considerations

Green product development under competition: A study of the fashion apparel industry

Motivated by the observed industrial issues, we analytically develop a fashion supply chain consisting of one manufacturer and two competing retailers and investigate how retail competition and consumer returns affect green product development in fashion apparel. In the basic model, that is, the pure “product greenness level” game, we find that the optimal greenness level of the fashion product decreases along with the level of market competition. This finding implies that a more competitive market leads to a lower optimal greenness level. We also identify that when the consumer return rate increases, the optimal product greenness level is substantially reduced. In the extended model with joint decisions on greenness and pricing, we find that the optimal product greenness level for the whole channel is always higher in the scenario when both retailers charge a higher retail price than in the case with a lower retail price. As such, the underdevelopment of green fashion products is a result of fashion industry features, such as an extremely competitive environment for green product development, relatively low retail prices for fashion products, and high consumer return rates. Therefore, fashion companies should join a co-opetition game for the green product market and simultaneously enhance their efficiency in managing consumer returns. To support our analytical findings, we conduct extensive industrial interviews with various representative companies. Based on this multi-methodological approach (MMA), this paper generates practice-relevant managerial insights that not only contribute to the literature, but also act as valuable references for industrialists

Pricing and Lead Time Decisions in a Duopoly Common Retailer Channel

This thesis studies a dual-level decentralized supply chain consisting of two suppliers and two retailers facing a price- and lead-time-sensitive demand. We model the suppliers' operations as M/M/1 queues and demand as a linear function of the retail prices and promised delivery lead-times offered to the customers. Three different kinds of games are constructed to analyze the pricing and lead-time decisions of the suppliers and retailers. We show the existence of a unique equilibrium in all games and provide the exact formulas to compute the optimal decisions for both the suppliers and retailers. We further present numerical examples to illustrate how the results of our model can be used to provide useful managerial insights for selecting the best strategies for suppliers and retailers under different market and operational environments

Services in Manufacturing Industries: Contributions to Quality and Competition

Motivated by the increasingly important role of services in manufacturing industries, this dissertation examines implications of this trend for quality management and competition by firms engaged in the production of joint product-service offerings. Broadly defined, we study the following research questions: How do the service contracts offered by manufacturers affect product quality? How does consumer demand respond to product quality and service attributes when manufacturers compete on services? How are consumer intentions influenced by product quality and service quality perceptions, and how does consumer heterogeneity influence this relationship? We empirically study these questions in the aerospace, automobile and consumer electronics industries, respectively. In the first study, we examine the impact of Performance-Based Contracting on product reliability in an application in the aerospace industry (aircraft engines), and show that the incentive alignment induced by performance-based contracts positively influences product reliability by different mechanisms. In the second essay, we formulate and estimate a structural model to analyze the impact of service competition and product quality in the U.S. automobile industry. We show that the impact of service attributes (warranty length, service quality) on consumer demand critically depends on the firm\u27s product quality. Finally, in the third essay (consumer electronics industry), we examine the joint influence of product quality and service quality perceptions on consumer intentions toward a brand, and show that consumer heterogeneity plays a significant role in defining this relationship. Collectively, our results suggest that the joint consideration of product and service is essential for the development of an effective competitive strategy and for the management of quality by manufacturing firms

Three Models for Pricing Decisions in Services or under Inventory Considerations

This dissertation studies pricing decisions under three different service settings. First, we consider a service system in which customers of two different types share the same service environment and their services are influenced by the presence of others. Specifically, when receiving services, customers interact with each other, and the effect of this interaction on the customers' utility may be positive or negative. Using a game-theoretic model, we show that in any Nash equilibrium, competing service providers will never benefit from price discrimination unless the externalities are negative and strong. With a numerical study, we find that when the two providers have small capacities, price discrimination will improve profits. However, when the two facilities have ample capacities, price discrimination might even hurt profits because of increased competition. The second setup is for a service system where competing service providers need to first perform an inspection to provide a quote to interested customers. We develop a game-theoretic model and fully characterize the equilibrium. With a numerical analysis, we find that, in equilibrium, firms might make profits mainly through the fees charged at the inspection stage. For the third setting, we consider the classical revenue management problem under inventory considerations with the additional feature that the firm has the option to bundle the product in clearance with a stable item. We prove that the optimal dynamic pricing strategy is of threshold-type, that is, it is optimal to offer a discount on the bundle when the value of an additional product is between two thresholds.Doctor of Philosoph

Emission regulations in the electricity market : an analysis from consumers, producers and central planner perspectives

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 119-122).In the first part of this thesis, the objective is to identify optimal bidding strategies in the wholesale electricity market. We consider asymmetric producers submitting bids to a system operator. The system operator allocates demand via a single clearing price auction. The highest accepted bid sets the per unit market price payed by consumers. We find a pure Nash equilibrium to the bidding strategies of asymmetric producers unattainable in a symmetric model. Our results show that producers with relatively large capacities are able to exercise market power. However, the market may seem competitive due to the large number of producers serving demand. The objective of the second part of the thesis, is to compare two regulation policies: a fixed transfer price, such as tax regulation, and a permit system, such as cap-and-trade. For this purpose, we analyze an economy where risk neutral manufacturers satisfy price sensitive demand. The objective of the regulation established by the central planner is to achieve an external objective, e.g. reduce pollution or limit consumption of scarce resource. When demand is uncertain, designing these regulations to achieve the same expected level of the external objective results in the same expected consumer price but very different manufacturers' expected profit and central planner revenue. For instance, our results show that when the firms are price takers, the manufacturers with the worst technology always prefer a tax policy. Interestingly, we identify conditions under which the manufacturers with the cleanest technology benefit from higher expected profit as tax rate increases. In the third part of the thesis, we investigate the impact labeling decisions have on the supply chain. We consider a two stage supply chain consisting of a supplier and a retailer. Demand is considered stochastic, decreasing in price and increasing in a quality parameter, e.g. carbon emissions. The unit production cost for the supplier is increasing in the quality level chosen. We identify two different contracts that maximize the efficiency of the supply chain while allowing the different parties to achieve their objectives individually.by Cristian Ricardo Figueroa Rodriguez.Ph.D

Dynamic Pricing and Inventory Management: Theory and Applications

We develop the models and methods to study the impact of some emerging trends in technology, marketplace, and society upon the pricing and inventory policy of a firm. We focus on the situation where the firm is in a dynamic, uncertain, and (possibly) competitive market environment. The market trends of particular interest to us are: (a) social networks, (b) sustainability concerns, and (c) customer behaviors. The two main running questions this dissertation aims to address are: (a) How these emerging market trends would influence the operations decisions and profitability of a firm; and (b) What pricing and inventory strategies a firm could use to leverage these trends. We also develop an effective comparative statics analysis method to address these two questions under different market trends. Overall, our results suggest that the current market trends of social networks, sustainability concerns, and customer behaviors have significant and interesting impact upon the operations policy of a firm, and that the firm could adopt some innovative pricing and inventory strategies to exploit these trends and substantially improve its profit. Our main findings are: (a) Network externalities (the monopoly setting). We find that network externalities prompt a firm to face the tradeoff between generating current profits and inducing future demands when making the price and inventory decisions, so that it should increase the base-stock level, and to decrease [increase] the sales price when the network size is small [large]. Our extensive numerical experiments also demonstrate the effectiveness of the heuristic policies that leverage network externalities by balancing generating current profits and inducing demands in the near future. (Chapter 2.) (b) Network externalities (the dynamic competition setting). In a competitive market with network externalities, the competing firms face the tradeoff between generating current profits and winning future market shares (i.e., the exploitation-induction tradeoff). We characterize the pure strategy Markov perfect equilibrium in both the simultaneous competition and the promotion-first competition. We show that, to balance the exploitation-induction tradeoff, the competing firms should increase promotional efforts, offer price discounts, and improve service levels. The exploitation-induction tradeoff could be a new driving force for the fat-cat effect (i.e., the equilibrium promotional efforts are higher under the promotion-first competition than those under the simultaneous competition). (Chapter 3.) (d) Trade-in remanufacturing. We show that, with the adoption of the very commonly used trade-in remanufacturing program, the firm may enjoy a higher profit with strategic customers than with myopic customers. Moreover, trade-in remanufacturing creates a tension between firm profitability and environmental sustainability with strategic customers, but benefits both the firm and the environment with myopic customers. We also find that, with either strategic or myopic customers, the socially optimal outcome can be achieved by using a simple linear subsidy and tax scheme. The commonly used government policy to subsidize for remanufacturing alone, however, does not induce the social optimum in general. (Chapter 4.) (d) Scarcity effect of inventory. We show that the scarcity effect drives both optimal prices and order-up-to levels down, whereas increased operational flexibilities (e.g., the inventory disposal and inventory withholding opportunities) mitigate the demand loss caused by high excess inventory and increase the optimal order-up-to levels and sales prices. Our extensive numerical studies also demonstrate that dynamic pricing leads to a much more significant profit improvement with the scarcity effect of inventory than without. (Chapter 5.) (e) Comparative statics analysis method. We develop a comparative statics method to study a general joint pricing and inventory management model with multiple demand segments, multiple suppliers, and stochastically evolving market conditions. Our new method makes componentwise comparisons between the focal decision variables under different parameter values, so it is capable of performing comparative statics analysis in a model where part of the decision variables are non-monotone, and it is well scalable. Hence, our new method is promising for comparative statics analysis in other operations management models. (Chapter 6.

Product Differentiation and Operations Strategy for Price and Time Sensitive Markets

In this dissertation, we study the interplay between a firm’s operations strategy, with regard to its capacity management, and its marketing decision of product differentiation. For this, we study a market comprising heterogeneous customers who differ in their preferences for time and price. Time sensitive customers are willing to pay a price premium for a shorter delivery time, while price sensitive customers are willing to accept a longer delivery time in return for a lower price. Firms exploit this heterogeneity in customers’ preferences, and offer a menu of products/services that differ only in their guaranteed delivery times and prices. From demand perspective, when customers are allowed to self-select according to their preferences, different products act as substitutes, affecting each other’s demand. Customized product for each segment, on the other hand, results in independent demand for each product. On the supply side, a firm may either share the same processing capacity to serve the two market segments, or may dicate capacity for each segment. Our objective is to understand the interaction between product substitution and the firm’s operations strategy (dedicated versus shared capacity), and how they shape the optimal product differentiation strategy. To address the above issue, we first study this problem for a single monopolist firm, which offers two versions of the same basic product: (i) regular product at a lower price but with a longer delivery time, and (ii) express product at a higher price but with a shorter delivery time. Demand for each product arrives according to a Poisson process with a rate that depends both on its price and delivery time. In addition, if the products are substitutable, each product’s demand is also influenced by the price and delivery time of the other product. Demands within each category are served on a first-come-first-serve basis. However, customers for express product are always given priority over the other category when they are served using shared resources. There is a standard delivery time for the regular product, and the firm’s objective is to appropriately price the two products and select the express delivery time so as to maximize its profit rate. The firm simultaneously needs to decide its installed processing capacity so as to meet its promised delivery times with a high degree of reliability. While the problem in a dedicated capacity setting is solved analytically, the same becomes very challenging in a shared capacity setting, especially in the absence of an analytical characterization of the delivery time distribution of regular customers in a priority queue. We develop a solution algorithm, using matrix geometric method in a cutting plane framework, to solve the problem numerically in a shared capacity setting. Our study shows that in a highly capacitated system, if the firm decides to move from a dedicated to a shared capacity setting, it will need to offer more differentiated products, whether the products are substitutable or not. In contrast, when customers are allowed to self-select, such that independent products become substitutable, a more homogeneous pricing scheme results. However, the effect of substitution on optimal delivery time differentiation depends on the firm’s capacity strategy and cost, as well as market characteristics. The optimal response to any change in capacity cost also depends on the firm’s operations strategy. In a dedicated capacity scenario, the optimal response to an increase in capacity cost is always to offer more homogeneous prices and delivery times. In a shared capacity setting, it is again optimal to quote more homogeneous delivery times, but increase or decrease the price differentiation depending on whether the status-quo capacity cost is high or low, respectively. We demonstrate that the above results are corroborated by real-life practices, and provide a number of managerial implications in terms of dealing with issues like volatile fuel prices. We further extend our study to a competitive setting with two firms, each of which may either share its processing capacities for the two products, or may dedicate capacity for each product. The demand faced by each firm for a given product now also depends on the price and delivery time quoted for the same product by the other firm. We observe that the qualitative results of a monopolistic setting also extend to a competitive setting. Specifically, in a highly capacitated system, the equilibrium prices and delivery times are such that they result in more differentiated products when both the firms use shared capacities as compared to the scenario when both the firms use dedicated capacities. When the competing firms are asymmetric, they exploit their distinctive characteristics to differentiate their products. Further, the effects of these asymmetries also depend on the capacity strategy used by the competing firms. Our numerical results suggest that the firm with expensive capacity always offers more homogeneous delivery times. However, its decision on how to differentiate its prices depends on the capacity setting of the two firms as well as the actual level of their capacity costs. On the other hand, the firm with a larger market base always offers more differentiated prices as well as delivery times, irrespective of the capacity setting of the competing firms

Response Time Reduction and Service Level Differentiation in Supply Chain Design: Models and Solution Approaches

Make-to-order (MTO) and assemble-to-order (ATO) systems are emerging business strategies in managing responsive supply chains, characterized by high product variety, highly variable customer demand, and short product life cycle. Motivated by the strategic importance of response time in today’s global business environment, this thesis presents models and solution approaches for response time reduction and service-level differentiation in designing MTO and ATO supply chains. In the first part, we consider the problem of response time reduction in the design of MTO supply chains. More specifically, we consider an MTO supply chain design model that seeks to simultaneously determine the optimal location and the capacity of distribution centers (DCs) and allocate stochastic customer demand to DCs, so as to minimize the response time in addition to the fixed cost of opening DCs and equipping them with sufficient assembly capacity and the variable cost of serving customers. The DCs are modelled as M/G/1 queues and response times are computed using steady-state waiting time results from queueing theory. The problem is set up as a network of spatially distributed M/G/1 queues and modelled as a nonlinear mixed-integer program. We linearize the model using a simple transformation and a piece-wise linear and concave approximation. We present two solution procedures: an exact solution approach based on cutting plane method and a Lagrangean heuristic for solving large instances of the problem. While the cutting plane approach provides the optimal solution for moderate instances in few iterations, the Lagrangean heuristic succeeds in finding feasible solutions for large instances that are within 5% from the optimal solution in reasonable computation times. We show that the solution procedure can be extended to systems with multiple customer classes. Using a computational study, we also show that substantial reduction in response times can be achieved with minimal increase in total costs in the design of responsive supply chains. Furthermore, we find the supply chain configuration (DC location, capacity, and demand allocation) that considers congestion and its effect on response time can be very different from the traditional configuration that ignores congestion. The second part considers the problem of response time reduction in the design of a two-echelon ATO supply chain, where a set of plants and DCs are to be established to distribute a set of finished products with non-trivial bill-of-materials to a set of customers with stochastic demand. The model is formulated as a nonlinear mixed integer programming problem. Lagrangean relaxation exploits the echelon structure of the problem to decompose into two subproblems - one for the make-tostock echelon and the other for the MTO echelon. We use the cutting plane based approach proposed above to solve the MTO echelon subproblem. While Lagrangean relaxation provides a lower bound, we present a heuristic that uses the solution of the subproblems to construct an overall feasible solution. Computational results reveal that the heuristic solution is on average within 6% from its optimal. In the final part of the thesis, we consider the problem of demand allocation and capacity selection in the design of MTO supply chains for segmented markets with service-level differentiated customers. Demands from each customer class arrives according to an independent Poisson process and the customers are served from shared DCs with finite capacity and generally distributed service times. Service-levels of various customer classes are expressed as the fraction of their demand served within a specified response (sojourn) time. Our objective is to determine the optimal location and the capacity of DCs and the demand allocation so as to minimize the sum of the fixed cost of opening DCs and equipping them with sufficient capacity and the variable cost of serving customers subject to service-level constraints for multiple customer classes. The problem is set up as a network of spatially distributed M/M/1 priority queues and modelled as a nonlinear mixed integer program. Due to the lack of closed form solution for service-level constraints for multiple classes, we present an iterative simulation-based cutting plane approach that relies on discrete-event simulation for the estimation of the service-level function and its subgradients. The subgradients obtained from the simulation are used to generate cuts that are appended to the mixed integer programming model. We also present a near-exact matrix analytic procedure to validate the estimates of the service-level function and its subgradients from the simulation. Our computational study shows that the method is robust and provides an optimal solution in most of the cases in reasonable computation time. Furthermore, using computational study, we examine the impact of different parameters on the design of supply chains for segmented markets and provide some managerial insights